Convex Formulation and Efficiency Enhancement for Powered Landing Guidance With Second-Order Cone Probability Constraints
Real-time trajectory optimization is crucial for achieving autonomous guidance in powered landing. However, the existing algorithms often struggle with uncertainties and are unable to handle second-order cone probability constraints, such as control magnitude and direction constraints. In addition,...
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| Vydáno v: | IEEE transactions on aerospace and electronic systems Ročník 61; číslo 2; s. 1742 - 1763 |
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| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
01.04.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 0018-9251, 1557-9603 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Real-time trajectory optimization is crucial for achieving autonomous guidance in powered landing. However, the existing algorithms often struggle with uncertainties and are unable to handle second-order cone probability constraints, such as control magnitude and direction constraints. In addition, the large-scale and complex nature of these optimization problems hampers real-time performance. This study addresses these shortcomings by presenting a convex formulation suitable for general second-order cone probability constraints and proposing two strategies, conservative approximation and variable reduction, to improve real-time performance. Specifically, the conservative approximation converts spectral norm constraints into second-order cone constraints, while the variable reduction reduces the number of optimization variables. Applied to a powered landing simulation scenario, the proposed approaches effectively handle second-order cone probability constraints and improve real-time performance by two to three orders of magnitude. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0018-9251 1557-9603 |
| DOI: | 10.1109/TAES.2024.3458940 |